app.py

from fastai.vision.all import *
import gradio as gr

learn = load_learner('architecturemodel.pkl')

categories = ('Achaemenid architecture',
 'American Foursquare architecture',
 'American craftsman style',
 'Ancient Egyptian architecture',
 'Art Deco architecture',
 'Art Nouveau architecture',
 'Baroque architecture',
 'Bauhaus architecture',
 'Beaux-Arts architecture',
 'Byzantine architecture',
 'Chicago school architecture',
 'Colonial architecture',
 'Deconstructivism',
 'Edwardian architecture',
 'Georgian architecture',
 'Gothic architecture',
 'Greek Revival architecture',
 'International style',
 'Novelty architecture',
 'Palladian architecture',
 'Postmodern architecture',
 'Queen Anne architecture',
 'Romanesque architecture',
 'Russian Revival architecture',
 'Tudor Revival architecture')

def classify_image(img):
    pred,idx,probs = learn.predict(img)
    return dict(zip(categories, map(float,probs)))

image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()
examples = ['bigben.jpeg','pyramid.jpeg','robiehouse.jpeg']

intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
intf.launch(inline=False, share=True)